Infrastructure Engineer – GPU/OpenShift

About the role

Lead and support next-generation Generative AI and Predictive AI platforms in a large-scale enterprise environment.

Tasks

• Design, deploy, and operate OpenShift platforms optimized for GPU workloads
• Support large-scale GPU SuperPod architectures and multi-node GPU clusters
• Manage AI/ML training, inference, and batch workloads
• Build observability and monitoring solutions using Grafana, Splunk, and enterprise telemetry tools
• Define SLIs/SLOs and improve platform reliability, performance, and resiliency
• Develop AI-driven automation and AIOps solutions for self-healing and incident remediation
• Lead production troubleshooting, root-cause analysis, and incident prevention
• Support highly available infrastructure, BCP/DR, and enterprise risk controls

Requirements

• 5+ years of infrastructure engineering experience
• 5+ years of Linux systems administration and troubleshooting
• 5+ years troubleshooting complex end-to-end architectures, including CI/CD pipelines
• 4+ years of AI/ML platform support experience
• 4+ years of Kubernetes/container platform experience, including production support
• Preferred: OpenShift in GPU-enabled, multi-tenant environments
• Preferred: GPU scheduling, quota management, and performance tuning
• Preferred: GPU SuperPod design and operations
• Preferred: Grafana, Splunk, and custom telemetry pipelines
• Preferred: Generative AI, Predictive AI, and AIOps automation
• Preferred: GCP and Azure AI/ML infrastructure
• Preferred: Hybrid/multi-cloud platforms, high availability, and disaster recovery
• Must be comfortable with onsite work from Day 1 and participation in a 24x7 on-call rotation.

Schedule

• Onsite from Day 1
• Monday–Friday
• Long-Term Contract
• Participation in a 24x7 on-call rotation

How to apply

• Share your updated resume by email.

Location

• Charlotte, NC
• Chandler, AZ
• Dallas, TX
• Iselin, NJ